/****************************************************************************************[Solver.h]
Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
Copyright (c) 2007-2010, Niklas Sorensson

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
associated documentation files (the "Software"), to deal in the Software without restriction,
including without limitation the rights to use, copy, modify, merge, publish, distribute,
sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or
substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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**************************************************************************************************/

#ifndef Minisat_Solver_h
#define Minisat_Solver_h

#include "minisat/core/SolverTypes.h"
#include "minisat/mtl/Alg.h"
#include "minisat/mtl/Heap.h"
#include "minisat/mtl/IntMap.h"
#include "minisat/mtl/Vec.h"
#include "minisat/utils/Options.h"

namespace Minisat {

//=================================================================================================
// Solver -- the main class:

class Solver
{
  public:
	// Constructor/Destructor:
	//
	Solver();
	virtual ~Solver();

	// Problem specification:
	//
	Var newVar(lbool upol = l_Undef, bool dvar = true); // Add a new variable with parameters specifying variable mode.
	void releaseVar(Lit l); // Make literal true and promise to never refer to variable again.

	bool addClause(const vec<Lit>& ps);			// Add a clause to the solver.
	bool addEmptyClause();						// Add the empty clause, making the solver contradictory.
	bool addClause(Lit p);						// Add a unit clause to the solver.
	bool addClause(Lit p, Lit q);				// Add a binary clause to the solver.
	bool addClause(Lit p, Lit q, Lit r);		// Add a ternary clause to the solver.
	bool addClause(Lit p, Lit q, Lit r, Lit s); // Add a quaternary clause to the solver.
	bool addClause_(vec<Lit>& ps); // Add a clause to the solver without making superflous internal copy. Will
								   // change the passed vector 'ps'.

	// Parallel support
	//
	void importClauses();
	void importUnitClauses();

	vec<Lit> importedClause;
	void* issuer; // used as the callback parameter

	// callback for clause learning
	void (*exportClauseCallback)(void*, vec<Lit>&);
	Lit (*importUnitCallback)(void*);
	bool (*importClauseCallback)(void*, vec<Lit>&);

	// Solving:
	//
	bool simplify();							 // Removes already satisfied clauses.
	bool solve(const vec<Lit>& assumps);		 // Search for a model that respects a given set of assumptions.
	lbool solveLimited(const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions (With
												 // resource constraints).
	bool solve();								 // Search without assumptions.
	bool solve(Lit p);							 // Search for a model that respects a single assumption.
	bool solve(Lit p, Lit q);					 // Search for a model that respects two assumptions.
	bool solve(Lit p, Lit q, Lit r);			 // Search for a model that respects three assumptions.
	bool okay() const;							 // FALSE means solver is in a conflicting state

	bool implies(const vec<Lit>& assumps, vec<Lit>& out);

	// Iterate over clauses and top-level assignments:
	ClauseIterator clausesBegin() const;
	ClauseIterator clausesEnd() const;
	TrailIterator trailBegin() const;
	TrailIterator trailEnd() const;

	void toDimacs(FILE* f, const vec<Lit>& assumps); // Write CNF to file in DIMACS-format.
	void toDimacs(const char* file, const vec<Lit>& assumps);
	void toDimacs(FILE* f, Clause& c, vec<Var>& map, Var& max);

	// Convenience versions of 'toDimacs()':
	void toDimacs(const char* file);
	void toDimacs(const char* file, Lit p);
	void toDimacs(const char* file, Lit p, Lit q);
	void toDimacs(const char* file, Lit p, Lit q, Lit r);

	// Variable mode:
	//
	void setPolarity(Var v, lbool b); // Declare which polarity the decision heuristic should use for a variable.
									  // Requires mode 'polarity_user'.
	void setDecisionVar(Var v,
						bool b); // Declare if a variable should be eligible for selection in the decision heuristic.
	void varBumpActivity(Var v, double inc); // Increase a variable by the given value.
	void varBumpActivity(Var v);			 // Increase a variable with the current 'bump' value.

	// Read state:
	//
	lbool value(Var x) const; // The current value of a variable.
	lbool value(Lit p) const; // The current value of a literal.
	lbool modelValue(
		Var x) const; // The value of a variable in the last model. The last call to solve must have been satisfiable.
	lbool modelValue(
		Lit p) const; // The value of a literal in the last model. The last call to solve must have been satisfiable.
	int nAssigns() const; // The current number of assigned literals.
	int nClauses() const; // The current number of original clauses.
	int nLearnts() const; // The current number of learnt clauses.
	int nVars() const;	  // The current number of variables.
	int nFreeVars() const;
	void printStats() const; // Print some current statistics to standard output.

	// Resource contraints:
	//
	void setConfBudget(int64_t x);
	void setPropBudget(int64_t x);
	void budgetOff();
	void interrupt();	   // Trigger a (potentially asynchronous) interruption of the solver.
	void clearInterrupt(); // Clear interrupt indicator flag.

	// Memory managment:
	//
	virtual void garbageCollect();
	void checkGarbage(double gf);
	void checkGarbage();

	// Extra results: (read-only member variable)
	//
	vec<lbool> model; // If problem is satisfiable, this vector contains the model (if any).
	LSet conflict;	  // If problem is unsatisfiable (possibly under assumptions),
					  // this vector represent the final conflict clause expressed in the assumptions.

	// Mode of operation:
	//
	int verbosity;
	double var_decay;
	double clause_decay;
	double random_var_freq;
	double random_seed;
	bool luby_restart;
	int ccmin_mode;		 // Controls conflict clause minimization (0=none, 1=basic, 2=deep).
	int phase_saving;	 // Controls the level of phase saving (0=none, 1=limited, 2=full).
	bool rnd_pol;		 // Use random polarities for branching heuristics.
	bool rnd_init_act;	 // Initialize variable activities with a small random value.
	double garbage_frac; // The fraction of wasted memory allowed before a garbage collection is triggered.
	int min_learnts_lim; // Minimum number to set the learnts limit to.

	int restart_first;	// The initial restart limit. (default 100)
	double restart_inc; // The factor with which the restart limit is multiplied in each restart. (default 1.5)
	double
		learntsize_factor; // The intitial limit for learnt clauses is a factor of the original clauses. (default 1 / 3)
	double learntsize_inc; // The limit for learnt clauses is multiplied with this factor each restart. (default 1.1)

	int learntsize_adjust_start_confl;
	double learntsize_adjust_inc;

	// Statistics: (read-only member variable)
	//
	uint64_t solves, starts, decisions, rnd_decisions, propagations, conflicts;
	uint64_t dec_vars, num_clauses, num_learnts, clauses_literals, learnts_literals, max_literals, tot_literals;

	bool remove_satisfied; // Indicates whether possibly inefficient linear scan for satisfied clauses should be
						   // performed in 'simplify'.

  protected:
	// Helper structures:
	//
	struct VarData
	{
		CRef reason;
		int level;
	};
	static inline VarData mkVarData(CRef cr, int l)
	{
		VarData d = { cr, l };
		return d;
	}

	struct Watcher
	{
		CRef cref;
		Lit blocker;
		Watcher(CRef cr, Lit p)
			: cref(cr)
			, blocker(p)
		{
		}
		bool operator==(const Watcher& w) const { return cref == w.cref; }
		bool operator!=(const Watcher& w) const { return cref != w.cref; }
	};

	struct WatcherDeleted
	{
		const ClauseAllocator& ca;
		WatcherDeleted(const ClauseAllocator& _ca)
			: ca(_ca)
		{
		}
		bool operator()(const Watcher& w) const { return ca[w.cref].mark() == 1; }
	};

	struct VarOrderLt
	{
		const IntMap<Var, double>& activity;
		bool operator()(Var x, Var y) const { return activity[x] > activity[y]; }
		VarOrderLt(const IntMap<Var, double>& act)
			: activity(act)
		{
		}
	};

	struct ShrinkStackElem
	{
		uint32_t i;
		Lit l;
		ShrinkStackElem(uint32_t _i, Lit _l)
			: i(_i)
			, l(_l)
		{
		}
	};

	// Solver state:
	//
	vec<CRef> clauses;	  // List of problem clauses.
	vec<CRef> learnts;	  // List of learnt clauses.
	vec<Lit> trail;		  // Assignment stack; stores all assigments made in the order they were made.
	vec<int> trail_lim;	  // Separator indices for different decision levels in 'trail'.
	vec<Lit> assumptions; // Current set of assumptions provided to solve by the user.

	VMap<double> activity; // A heuristic measurement of the activity of a variable.
	VMap<lbool> assigns;   // The current assignments.
	VMap<char> polarity;   // The preferred polarity of each variable.
	VMap<lbool> user_pol;  // The users preferred polarity of each variable.
	VMap<char> decision;   // Declares if a variable is eligible for selection in the decision heuristic.
	VMap<VarData> vardata; // Stores reason and level for each variable.
	OccLists<Lit, vec<Watcher>, WatcherDeleted, MkIndexLit>
		watches; // 'watches[lit]' is a list of constraints watching 'lit' (will go there if literal becomes true).

	Heap<Var, VarOrderLt> order_heap; // A priority queue of variables ordered with respect to the variable activity.

	bool ok;			// If FALSE, the constraints are already unsatisfiable. No part of the solver state may be used!
	double cla_inc;		// Amount to bump next clause with.
	double var_inc;		// Amount to bump next variable with.
	int qhead;			// Head of queue (as index into the trail -- no more explicit propagation queue in MiniSat).
	int simpDB_assigns; // Number of top-level assignments since last execution of 'simplify()'.
	int64_t simpDB_props; // Remaining number of propagations that must be made before next execution of 'simplify()'.
	double progress_estimate; // Set by 'search()'.

	Var next_var; // Next variable to be created.
	ClauseAllocator ca;

	vec<Var> released_vars;
	vec<Var> free_vars;

	// Temporaries (to reduce allocation overhead). Each variable is prefixed by the method in which it is
	// used, exept 'seen' wich is used in several places.
	//
	VMap<char> seen;
	vec<ShrinkStackElem> analyze_stack;
	vec<Lit> analyze_toclear;
	vec<Lit> add_tmp;

	double max_learnts;
	double learntsize_adjust_confl;
	int learntsize_adjust_cnt;

	// Resource contraints:
	//
	int64_t conflict_budget;	// -1 means no budget.
	int64_t propagation_budget; // -1 means no budget.
	bool asynch_interrupt;

	// Main internal methods:
	//
	void insertVarOrder(Var x);							  // Insert a variable in the decision order priority queue.
	Lit pickBranchLit();								  // Return the next decision variable.
	void newDecisionLevel();							  // Begins a new decision level.
	void uncheckedEnqueue(Lit p, CRef from = CRef_Undef); // Enqueue a literal. Assumes value of literal is undefined.
	bool enqueue(Lit p, CRef from = CRef_Undef); // Test if fact 'p' contradicts current state, enqueue otherwise.
	CRef propagate();							 // Perform unit propagation. Returns possibly conflicting clause.
	void cancelUntil(int level);				 // Backtrack until a certain level.
	void analyze(CRef confl, vec<Lit>& out_learnt, int& out_btlevel); // (bt = backtrack)
	void analyzeFinal(
		Lit p,
		LSet& out_conflict);  // COULD THIS BE IMPLEMENTED BY THE ORDINARIY "analyze" BY SOME REASONABLE GENERALIZATION?
	bool litRedundant(Lit p); // (helper method for 'analyze()')
	lbool search(int nof_conflicts);	 // Search for a given number of conflicts.
	lbool solve_();						 // Main solve method (assumptions given in 'assumptions').
	void reduceDB();					 // Reduce the set of learnt clauses.
	void removeSatisfied(vec<CRef>& cs); // Shrink 'cs' to contain only non-satisfied clauses.
	void rebuildOrderHeap();

	// Maintaining Variable/Clause activity:
	//
	void varDecayActivity(); // Decay all variables with the specified factor. Implemented by increasing the 'bump'
							 // value instead.
	void claDecayActivity(); // Decay all clauses with the specified factor. Implemented by increasing the 'bump' value
							 // instead.
	void claBumpActivity(Clause& c); // Increase a clause with the current 'bump' value.

	// Operations on clauses:
	//
	void attachClause(CRef cr);						 // Attach a clause to watcher lists.
	void detachClause(CRef cr, bool strict = false); // Detach a clause to watcher lists.
	void removeClause(CRef cr);						 // Detach and free a clause.
	bool isRemoved(CRef cr) const;					 // Test if a clause has been removed.
	bool locked(
		const Clause& c) const; // Returns TRUE if a clause is a reason for some implication in the current state.
	bool satisfied(const Clause& c) const; // Returns TRUE if a clause is satisfied in the current state.

	// Misc:
	//
	int decisionLevel() const;			 // Gives the current decisionlevel.
	uint32_t abstractLevel(Var x) const; // Used to represent an abstraction of sets of decision levels.
	CRef reason(Var x) const;
	int level(Var x) const;
	double progressEstimate() const; // DELETE THIS ?? IT'S NOT VERY USEFUL ...
	bool withinBudget() const;
	void relocAll(ClauseAllocator& to);

	// Static helpers:
	//

	// Returns a random float 0 <= x < 1. Seed must never be 0.
	static inline double drand(double& seed)
	{
		seed *= 1389796;
		int q = (int)(seed / 2147483647);
		seed -= (double)q * 2147483647;
		return seed / 2147483647;
	}

	// Returns a random integer 0 <= x < size. Seed must never be 0.
	static inline int irand(double& seed, int size) { return (int)(drand(seed) * size); }
};

//=================================================================================================
// Implementation of inline methods:

inline CRef
Solver::reason(Var x) const
{
	return vardata[x].reason;
}
inline int
Solver::level(Var x) const
{
	return vardata[x].level;
}

inline void
Solver::insertVarOrder(Var x)
{
	if (!order_heap.inHeap(x) && decision[x])
		order_heap.insert(x);
}

inline void
Solver::varDecayActivity()
{
	var_inc *= (1 / var_decay);
}
inline void
Solver::varBumpActivity(Var v)
{
	varBumpActivity(v, var_inc);
}
inline void
Solver::varBumpActivity(Var v, double inc)
{
	if ((activity[v] += inc) > 1e100) {
		// Rescale:
		for (int i = 0; i < nVars(); i++)
			activity[i] *= 1e-100;
		var_inc *= 1e-100;
	}

	// Update order_heap with respect to new activity:
	if (order_heap.inHeap(v))
		order_heap.decrease(v);
}

inline void
Solver::claDecayActivity()
{
	cla_inc *= (1 / clause_decay);
}
inline void
Solver::claBumpActivity(Clause& c)
{
	if ((c.activity() += cla_inc) > 1e20) {
		// Rescale:
		for (int i = 0; i < learnts.size(); i++)
			ca[learnts[i]].activity() *= 1e-20;
		cla_inc *= 1e-20;
	}
}

inline void
Solver::checkGarbage(void)
{
	return checkGarbage(garbage_frac);
}
inline void
Solver::checkGarbage(double gf)
{
	if (ca.wasted() > ca.size() * gf)
		garbageCollect();
}

// NOTE: enqueue does not set the ok flag! (only public methods do)
inline bool
Solver::enqueue(Lit p, CRef from)
{
	return value(p) != l_Undef ? value(p) != l_False : (uncheckedEnqueue(p, from), true);
}
inline bool
Solver::addClause(const vec<Lit>& ps)
{
	ps.copyTo(add_tmp);
	return addClause_(add_tmp);
}
inline bool
Solver::addEmptyClause()
{
	add_tmp.clear();
	return addClause_(add_tmp);
}
inline bool
Solver::addClause(Lit p)
{
	add_tmp.clear();
	add_tmp.push(p);
	return addClause_(add_tmp);
}
inline bool
Solver::addClause(Lit p, Lit q)
{
	add_tmp.clear();
	add_tmp.push(p);
	add_tmp.push(q);
	return addClause_(add_tmp);
}
inline bool
Solver::addClause(Lit p, Lit q, Lit r)
{
	add_tmp.clear();
	add_tmp.push(p);
	add_tmp.push(q);
	add_tmp.push(r);
	return addClause_(add_tmp);
}
inline bool
Solver::addClause(Lit p, Lit q, Lit r, Lit s)
{
	add_tmp.clear();
	add_tmp.push(p);
	add_tmp.push(q);
	add_tmp.push(r);
	add_tmp.push(s);
	return addClause_(add_tmp);
}

inline bool
Solver::isRemoved(CRef cr) const
{
	return ca[cr].mark() == 1;
}
inline bool
Solver::locked(const Clause& c) const
{
	return value(c[0]) == l_True && reason(var(c[0])) != CRef_Undef && ca.lea(reason(var(c[0]))) == &c;
}
inline void
Solver::newDecisionLevel()
{
	trail_lim.push(trail.size());
}

inline int
Solver::decisionLevel() const
{
	return trail_lim.size();
}
inline uint32_t
Solver::abstractLevel(Var x) const
{
	return 1 << (level(x) & 31);
}
inline lbool
Solver::value(Var x) const
{
	return assigns[x];
}
inline lbool
Solver::value(Lit p) const
{
	return assigns[var(p)] ^ sign(p);
}
inline lbool
Solver::modelValue(Var x) const
{
	return model[x];
}
inline lbool
Solver::modelValue(Lit p) const
{
	return model[var(p)] ^ sign(p);
}
inline int
Solver::nAssigns() const
{
	return trail.size();
}
inline int
Solver::nClauses() const
{
	return num_clauses;
}
inline int
Solver::nLearnts() const
{
	return num_learnts;
}
inline int
Solver::nVars() const
{
	return next_var;
}
// TODO: nFreeVars() is not quite correct, try to calculate right instead of adapting it like below:
inline int
Solver::nFreeVars() const
{
	return (int)dec_vars - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]);
}
inline void
Solver::setPolarity(Var v, lbool b)
{
	user_pol[v] = b;
}
inline void
Solver::setDecisionVar(Var v, bool b)
{
	if (b && !decision[v])
		dec_vars++;
	else if (!b && decision[v])
		dec_vars--;

	decision[v] = b;
	insertVarOrder(v);
}
inline void
Solver::setConfBudget(int64_t x)
{
	conflict_budget = conflicts + x;
}
inline void
Solver::setPropBudget(int64_t x)
{
	propagation_budget = propagations + x;
}
inline void
Solver::interrupt()
{
	asynch_interrupt = true;
}
inline void
Solver::clearInterrupt()
{
	asynch_interrupt = false;
}
inline void
Solver::budgetOff()
{
	conflict_budget = propagation_budget = -1;
}
inline bool
Solver::withinBudget() const
{
	return !asynch_interrupt && (conflict_budget < 0 || conflicts < (uint64_t)conflict_budget) &&
		   (propagation_budget < 0 || propagations < (uint64_t)propagation_budget);
}

// FIXME: after the introduction of asynchronous interrruptions the solve-versions that return a
// pure bool do not give a safe interface. Either interrupts must be possible to turn off here, or
// all calls to solve must return an 'lbool'. I'm not yet sure which I prefer.
inline bool
Solver::solve()
{
	budgetOff();
	assumptions.clear();
	return solve_() == l_True;
}
inline bool
Solver::solve(Lit p)
{
	budgetOff();
	assumptions.clear();
	assumptions.push(p);
	return solve_() == l_True;
}
inline bool
Solver::solve(Lit p, Lit q)
{
	budgetOff();
	assumptions.clear();
	assumptions.push(p);
	assumptions.push(q);
	return solve_() == l_True;
}
inline bool
Solver::solve(Lit p, Lit q, Lit r)
{
	budgetOff();
	assumptions.clear();
	assumptions.push(p);
	assumptions.push(q);
	assumptions.push(r);
	return solve_() == l_True;
}
inline bool
Solver::solve(const vec<Lit>& assumps)
{
	budgetOff();
	assumps.copyTo(assumptions);
	return solve_() == l_True;
}
inline lbool
Solver::solveLimited(const vec<Lit>& assumps)
{
	assumps.copyTo(assumptions);
	return solve_();
}
inline bool
Solver::okay() const
{
	return ok;
}

inline ClauseIterator
Solver::clausesBegin() const
{
	return ClauseIterator(ca, &clauses[0]);
}
inline ClauseIterator
Solver::clausesEnd() const
{
	return ClauseIterator(ca, &clauses[clauses.size()]);
}
inline TrailIterator
Solver::trailBegin() const
{
	return TrailIterator(&trail[0]);
}
inline TrailIterator
Solver::trailEnd() const
{
	return TrailIterator(&trail[decisionLevel() == 0 ? trail.size() : trail_lim[0]]);
}

inline void
Solver::toDimacs(const char* file)
{
	vec<Lit> as;
	toDimacs(file, as);
}
inline void
Solver::toDimacs(const char* file, Lit p)
{
	vec<Lit> as;
	as.push(p);
	toDimacs(file, as);
}
inline void
Solver::toDimacs(const char* file, Lit p, Lit q)
{
	vec<Lit> as;
	as.push(p);
	as.push(q);
	toDimacs(file, as);
}
inline void
Solver::toDimacs(const char* file, Lit p, Lit q, Lit r)
{
	vec<Lit> as;
	as.push(p);
	as.push(q);
	as.push(r);
	toDimacs(file, as);
}

//=================================================================================================
// Debug etc:

//=================================================================================================
}

#endif
